This disclosure incorporates by reference a computer program listing appendix on compact disk and having 1 disk and one duplicate disk and each disk having the following files: M-7229-1, having Appendices A to G; the assignee of this application reserves all copyright rights on the content of this computer program listing.
A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by any one of the patent disclosure, as it appears in the Patent and Trademark office patent files or records, but otherwise reserves all copyright rights whatsoever. 37 CFR xc2xa71.71.
1. Field of the Invention
The invention relates to the detection of defects in patterned substrates, such as semiconductor wafers, particularly based on features in voltage-contrast images.
2. The Prior Art
Manufacture of semiconductor devices involves many process steps resulting in patterns on a substrate. If the patterns of an intermediate stage of production are defective, they can result in defective die and, thus, low yields. Methods and apparatus for inspecting the patterns on semiconductor wafers at intermediate stages of production (xe2x80x9cin-processxe2x80x9d) are known. These include systems and methods based on identification of pattern defects visible in optical images of the wafer. At least one approach is based on voltage-contrast images of the wafer acquired using a scanning electron beam, as described in U.S. Pat. Nos. 5,502,306 and 5,578,821 and implemented in the SEMSpec system offered commercially by KLA-Tencor Corp.
A prior method for detecting defects from voltage-contrast images is based on differencing of pixel-intensity values, pixel-by-pixel, between an image of the pattern to be inspected and a reference image. In this method, two voltage-contrast images, or two regions of one voltage-contrast image, are compared. To extract defects, the two images or image regions are first corrected for differences in brightness and contrast and aligned with one another. Then the difference of pixel-intensity values is taken, pixel-by-pixel, to produce a difference image. The resulting difference image is thresholded to produce a defect image in which the pixel values are binary. Features in the defect image meeting certain conditions, such as minimum size, shape, intensity, etc., are considered defects. Statistics of the defects in the images are then computed and reported. For example, the largest defect and total number of defects might be returned for each image. Then the images are reviewed based upon these statistics so that the most significant defects are processed and analyzed first, thereby reducing the review time considerably.
A strength of this method is that it requires little knowledge of electrical features or structures in the voltage-contrast images, only that they are of the same approximate size in both images or image regions and that alignment and image normalization will correct the overall differences in the images or image regions. This method allows voltage-contrast defects to be detected without first knowing what electrical patterns are being inspected.
But this strength is also a weakness: all image differences are considered potential defects even if they are not, so it is not possible to differentiate xe2x80x9ckillerxe2x80x9d defects from xe2x80x9cnuisancexe2x80x9d defects or xe2x80x9cfalsexe2x80x9d defects. A xe2x80x9ckillerxe2x80x9d defect is a defect of electrical significance in final test of a die, leading to reduced reliability or reduced electrical performance. A xe2x80x9cfalsexe2x80x9d defect is a report from a defect detection system of a defect which does not correspond to any surface or image artifact, resulting for example from an error by the defect system. A xe2x80x9cnuisancexe2x80x9d defect is a surface or image artifact which is real but is not a killer defect or otherwise of interest. Some artifacts of the inspection process are due to image misalignment, local image distortions and non-linearities of the scanning process used to acquire the voltage-contrast images. Since the occurrence of killer defects is in general quite rare, the number of nuisance defects detected can be much larger than the number of killer defects. In conventional, pixel-based inspection systems, 90% or more of the reported defects can be nuisance defects. Separating these from the killer defects requires time-consuming and costly human review and judgment. The high rate of nuisance defects and false defects and need for human intervention make it difficult to improve the performance of the inspection process to make it more useful in semiconductor wafer fabrication. Existing solutions to reduce the rate of nuisance defects and false defects caused by misalignment, such as precise wafer-stage positioning, more uniform and repeatable imaging, and improved defect-detection algorithms, do not eliminate the problem and typically reduce sensitivity to killer defects. At the same time, these solutions require more processing, and thus more processing time or more processing hardware. This limits throughput and the performance vs. price ratio.
Another drawback is that, since the method is pixel-based, it can only detect differences of intensity pixel-by-pixel. This makes detection of certain types of defects difficult if not impossible. Co-pending U.S. patent application Ser. No. 09/226,962 describes techniques for enhancing the visibility in a voltage-contrast image of electrically-significant defects in features such as unfilled contact holes. These techniques cause a change in the apparent size of the unfilled contact hole in the voltage-contrast image depending on electrical connectivity of material in the contact hole. While a pixel-based image-comparison method might detect the change in size as an intensity difference for pixels surrounding the contact hole, and pixel-intensity differencing might show a doughnut-shaped defect, it would not reveal the fundamental manifestation of this type of defectxe2x80x94an apparent change of size of the feature rather than a change of intensity.
FIG. 1 shows a prior method in which images are acquired and processed in parallel. The image acquisition portion begins with setup of a batch file at step 105, followed by image acquisition at step 110, storage of the image at step 115, and moving to a next image at step 120. Images are stored in a disk storage device 125. Steps 110, 115 and 120 are repeated for other regions of a wafer and, when imaging of the wafer is complete, imaging of another wafer begins. Once an image has been acquired, image processing proceeds in parallel with acquisition of further images. Image processing begins with alignment of the acquired image with a reference image at step 130, then the pixel-intensity levels of the images are differenced at step 135 to produce a difference image. Noise is reduced from the difference image at step 140, followed by counting of features in the difference image at step 145. Features in the difference image are sorted at step 150, and manually reviewed at step 155 to decide which of the features are to be considered defects.
Methods and apparatus are desired which will offer a lower rate of nuisance defects and less need for human intervention, and thus improved throughput and performance vs. cost.
Methods and apparatus consistent with the invention employ feature-based image processing to detect, quantify and analyze defects in inspection of patterned substrates, such as semiconductor wafers, from voltage contrast e-beam images. A method of inspecting a patterned substrate comprises: preparing a reference image and a test image, extracting features from the reference image and extracting features from the test image, matching features of the reference image and features of the test image, and comparing features of the reference image and of the test image to identify defects. The images can be aligned before matching features. The reference image can be a voltage-contrast image of a first patterned substrate and the test image a voltage-contrast image of a second substrate, or the reference image can be a voltage-contrast image of a first region of a patterned substrate and the test image a voltage-contrast image of a second region of the same patterned substrate, or the reference image can be an image of repeating cells of a patterned substrate and the test image a duplicate of the reference image shifted by one cell relative to the reference image. The images can be pre-processed to reduce noise and/or artifacts such as by spatial smoothing, and/or normalizing. Comparing features of the images to identify defects can comprise computing feature properties (such as size, shape, average pixel intensity, center of gravity, diameter, area, standard deviation, etc.), comparing computed feature properties, and determining comparison results which meet predetermined defect criteria. Extracting features from an image can comprise enhancing the features (such as by computing an average background level of the image and removing the average background level from the image) to produce a first modified image, thresholding the first modified image to produce a second modified image, and identifying features in the second modified image. Alternatively, extracting features from an image can comprise matching a feature template in the image and identifying features in the image that match the feature-template.
Embodiments consistent with the invention include apparatus for inspecting patterned substrates, computer-readable media containing instructions for controlling a system having a processor for inspecting patterned substrates, and computer program products comprising a computer usable media having computer-readable program code embodied therein for controlling a system for inspecting patterned substrates.
These and other features of embodiments consistent with the invention will become apparent to those of skill in the art from the following description and the accompanying drawing figures.